scholarly journals Motion coordination for humanoid jumping using maximized joint power

2021 ◽  
Vol 13 (6) ◽  
pp. 168781402110284
Author(s):  
Xuechao Chen ◽  
Wenxi Liao ◽  
Zhangguo Yu ◽  
Haoxiang Qi ◽  
Xinyang Jiang ◽  
...  
Keyword(s):  
Output Power ◽  
Humanoid Robot ◽  
Humanoid Robots ◽  
Optimization Method ◽  
Motion Coordination ◽  
Joint Power ◽  
Simulation And Experiment ◽  
Solid Foundation ◽  
Environmental Adaptability ◽  
Practical Factors

Jumping capability of humanoid robots can be considered as one of the cruxes to improve the performance of future humanoid robot applications. This paper presents an optimization method on a three-linkage system to achieve a jumping behavior, which is followed by the clarification of the mathematical modeling and motor-joint model with practical factors considered. In consideration of the constraints of ZMP and the performance of the motor, the output power of the joint motors is maximized as much as possible to achieve a higher height. Finally, the optimization method is verified by the simulation and experiment. Different from other electric driven robots, which take the output power of the joint as the constraint, we maximize the output power of the joint to optimize the hopping performance of the robot. Realizing dynamic jumping of humanoid robots can also provide a solid foundation for further research on running, which can greatly enhance the environmental adaptability.

scholarly journals Gait Optimization Method for Humanoid Robots Based on Parallel Comprehensive Learning Particle Swarm Optimizer Algorithm

2021 ◽  
Vol 14 ◽  
Author(s):  
Chongben Tao ◽  
Jie Xue ◽  
Zufeng Zhang ◽  
Feng Cao ◽  
Chunguang Li ◽  
...  
Keyword(s):  
Humanoid Robot ◽  
Group Structure ◽  
Particle Swarm ◽  
Humanoid Robots ◽  
Optimization Method ◽  
Gait Training ◽  
Walking Ability ◽  
Particle Swarm Optimizer ◽  
Training Environment ◽  
Gait Optimization

To improve the fast and stable walking ability of a humanoid robot, this paper proposes a gait optimization method based on a parallel comprehensive learning particle swarm optimizer (PCLPSO). Firstly, the key parameters affecting the walking gait of the humanoid robot are selected based on the natural zero-moment point trajectory planning method. Secondly, by changing the slave group structure of the PCLPSO algorithm, the gait training task is decomposed, and a parallel distributed multi-robot gait training environment based on RoboCup3D is built to automatically optimize the speed and stability of bipedal robot walking. Finally, a layered learning approach is used to optimize the turning ability of the humanoid robot. The experimental results show that the PCLPSO algorithm achieves a quickly optimal solution, and the humanoid robot optimized possesses a fast and steady gait and flexible steering ability.

AN EVOLUTIONARY OPTIMIZED FOOTSTEP PLANNER FOR THE NAVIGATION OF HUMANOID ROBOTS

2012 ◽  
Vol 09 (01) ◽  
pp. 1250005 ◽  
Author(s):  
YOUNG-DAE HONG ◽  
JONG-HWAN KIM
Keyword(s):  
Humanoid Robot ◽  
Humanoid Robots ◽  
Step Length ◽  
Pattern Generator ◽  
Elapsed Time ◽  
Mechanical Constraints ◽  
Walking Pattern ◽  
Simulation And Experiment ◽  
The Given ◽  
Navigation Method

In this paper, an evolutionary optimized footstep planner for the navigation of humanoid robots is proposed. A footstep planner based on a univector field navigation method is proposed to generate a command state (CS) as an input to a modifiable walking pattern generator (MWPG) at each footstep. The MWPG generates associated trajectories of every leg joint to follow the given CS. In order to satisfy various objectives in the navigation, the univector fields are optimized by evolutionary programming. The three objectives, shortest elapsed time to get to a destination, safety without obstacle collision, and less energy consumption, are considered with mechanical constraints of a real humanoid robot, that is, the maximum step length and allowable yawing range of the feet. The effectiveness of the proposed algorithm is demonstrated through both computer simulation and experiment for a small-sized humanoid robot, HanSaRam-IX.

AN ANALYTICAL METHOD FOR REAL-TIME GAIT PLANNING FOR HUMANOID ROBOTS

2006 ◽  
Vol 03 (01) ◽  
pp. 1-19 ◽  
Author(s):  
KENSUKE HARADA ◽  
SHUUJI KAJITA ◽  
KENJI KANEKO ◽  
HIROHISA HIRUKAWA
Keyword(s):  
Real Time ◽  
Analytical Method ◽  
Humanoid Robot ◽  
Humanoid Robots ◽  
Center Of Gravity ◽  
Gait Planning ◽  
The Real ◽  
Smooth Change ◽  
Simulation And Experiment ◽  
Zero Moment

This paper studies real-time gait planning for a humanoid robot. By simultaneously planning the trajectories of the COG (Center of Gravity) and the ZMP (Zero Moment Point), a fast and smooth change of gait can be realized. The change of gait is also realized by connecting the newly calculated trajectories to the current ones. While we propose two methods for connecting two trajectories, i.e. the real-time method and the quasi-real-time one, we show that a stable change of gait can be realized by using the quasi-real-time method even if the change of the step position is significant. The effectiveness of the proposed methods are confirmed by simulation and experiment.

scholarly journals SIMULATION AND ANALYZES OF INVERSE-KINEMATIC MODEL OF HUMANOID ROBOT HAND

2019 ◽  
pp. 117-122
Author(s):  
Martin Varga ◽  
Filip Filakovský ◽  
Ivan Virgala
Keyword(s):  
Numerical Modeling ◽  
Humanoid Robot ◽  
Least Squares Method ◽  
Mechanical Design ◽  
Kinematic Model ◽  
Humanoid Robots ◽  
Optimization Method ◽  
Inverse Kinematic ◽  
Robot Hand ◽  
Kinematic Modeling

Urgency of the research. Nowadays robotics and mechatronics come to be mainstream. With development in these areas also grow computing fastidiousness. Since there is significant focus on numerical modeling and algorithmization in kinematic and dynamic modeling. Target setting. Suitable approach for numerical modeling is important from the view of time consumption as well as stability of computing. Actual scientific researches and issues analysis. Designing and modeling of humanoid robots have high interest in the field of robotics. The hardware and mechanical design of robots is on significantly higher level in comparison with software of robots. So, modeling and control of robots is in the interest of researchers. Uninvestigated parts of general matters defining. Comparison of methods for numerical modeling of inverse kinematics. The research objective. Comparing four methods from the view of performance and stability. The statement of basic materials. This paper investigates the area of kinematic modeling of humanoid robot hand and simulation in MATLAB. Conclusions. The paper investigated inverse kinematic model approaches. There were analyzed pseudoinverse method, transpose of Jacobian method, damped least squares method as an optimization method. The results of the simulations show the advantages of optimization method. During the simulations it never fail in comparison with other tested methods.

scholarly journals Rolling Optimization Method for Humanoid Robots

2015 ◽  
Vol 20 (2) ◽  
pp. 78
Author(s):  
Riadh Zaier
Keyword(s):  
Humanoid Robot ◽  
Humanoid Robots ◽  
Optimization Method ◽  
Initial Value ◽  
Walking Motion ◽  
Zero Moment ◽  
Rolling Optimization ◽  
Single Support Phase ◽  
Locomotion Controller ◽  
Support Phase

In this paper, a method of optimizing the rolling amplitude needed for a stable and smooth walking movement of a humanoid robot is considered. The optimization algorithm was based on minimizing a cost function defined by the rolling overshoot. The amplitude of the rolling during locomotion was calculated using the lateral zero moment point (ZMP) position. The initial value of the rolling was the static rolling that corresponds to the position of the ZMP at the center of the support polygon. The algorithm consisted of performing a ZMP calculation at two points that correspond to single support phases. Simplifying the robot as an inverted pendulum, the gyro feedback controller parameters were tuned to have a passive-like walking motion and a faster response of the robot state to the equilibrium point at single support phase. Experimental results, using HOAP-3 of Fujitsu, showed that the algorithm was successfully implemented along with the locomotion controller. With the optimal rolling technique, the humanoid robot could exhibit a stable and smooth walking movement.  

Humans and humanoids

2018 ◽  
Author(s):  
Giorgio Metta
Keyword(s):  
Humanoid Robot ◽  
Robot Vision ◽  
Physical Space ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Humanoid Robotics ◽  
Biomimetic Robot ◽  
Compliant Actuation

This chapter outlines a number of research lines that, starting from the observation of nature, attempt to mimic human behavior in humanoid robots. Humanoid robotics is one of the most exciting proving grounds for the development of biologically inspired hardware and software—machines that try to recreate billions of years of evolution with some of the abilities and characteristics of living beings. Humanoids could be especially useful for their ability to “live” in human-populated environments, occupying the same physical space as people and using tools that have been designed for people. Natural human–robot interaction is also an important facet of humanoid research. Finally, learning and adapting from experience, the hallmark of human intelligence, may require some approximation to the human body in order to attain similar capacities to humans. This chapter focuses particularly on compliant actuation, soft robotics, biomimetic robot vision, robot touch, and brain-inspired motor control in the context of the iCub humanoid robot.

DESIGN AND SIMULATION OF A 1-DOF ANTHROPOMORPHIC CLUTCHED ARM FOR HUMANOID ROBOTS

2010 ◽  
Vol 07 (01) ◽  
pp. 157-182 ◽  
Author(s):  
HAO GU ◽  
MARCO CECCARELLI ◽  
GIUSEPPE CARBONE
Keyword(s):  
Humanoid Robot ◽  
Humanoid Robots ◽  
Robot Arm ◽  
Dynamic Simulations ◽  
Suitable Combination ◽  
User Friendly

In this paper, problems for an anthropomorphic robot arm are approached for an application in a humanoid robot with the specific features of cost oriented design and user-friendly operation. One DOF solution is proposed by using a suitable combination of gearing systems, clutches, and linkages. Models and dynamic simulations are used both for designing the system and checking the operation feasibility.

scholarly journals User-centred design of humanoid robots’ communication

2020 ◽  
Vol 12 (1) ◽  
pp. 58-73
Author(s):  
Sofia Thunberg ◽  
Tom Ziemke
Keyword(s):  
Mental Models ◽  
Participatory Design ◽  
Humanoid Robot ◽  
State Of The Art ◽  
Design Method ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Design Concepts ◽  
Design Ideas

AbstractInteraction between humans and robots will benefit if people have at least a rough mental model of what a robot knows about the world and what it plans to do. But how do we design human-robot interactions to facilitate this? Previous research has shown that one can change people’s mental models of robots by manipulating the robots’ physical appearance. However, this has mostly not been done in a user-centred way, i.e. without a focus on what users need and want. Starting from theories of how humans form and adapt mental models of others, we investigated how the participatory design method, PICTIVE, can be used to generate design ideas about how a humanoid robot could communicate. Five participants went through three phases based on eight scenarios from the state-of-the-art tasks in the RoboCup@Home social robotics competition. The results indicate that participatory design can be a suitable method to generate design concepts for robots’ communication in human-robot interaction.

Development of Foot Structure for Humanoid Robot Using Topology Optimization

2018 ◽  
Vol 29 ◽  
pp. 34-45
Author(s):  
Van Tinh Nguyen ◽  
Daichi Kiuchi ◽  
Hiroshi Hasegawa
Keyword(s):  
Topology Optimization ◽  
Humanoid Robot ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Gait Pattern ◽  
Surface Model ◽  
Foot Structure ◽  
Adaptive Differential Evolution ◽  
Reaction Forces ◽  
Set Up

This paper addresses the development of a foot structure for 22-Degree of Freedom (DoF) humanoid robot. The goal of this research is to reduce the weight of the foot and enable the robot to walk steadily. The proposed foot structure is based on the consideration of cases where the ground reaction forces are set up in different situations. The optimal foot structure is a combination of all the topology optimization results. Additionally, a gait pattern is generated by an approximated optimization method based on Response Surface Model (RSM) and Improved Self-Adaptive Differential Evolution Algorithm (ISADE). The result is validated through dynamic simulation by a commercially available software called Adams (MSC software, USA) with the humanoid robot named KHR-3HV belonging to Kondo Kagaku company.

The Pransky interview: Dr Jun Ho Oh, Professor and Director of Humanoid Robot Research Center, KAIST; Cofounder, Rainbow Robotics Co.

2017 ◽  
Vol 44 (6) ◽  
pp. 695-699
Author(s):  
Joanne Pransky
Keyword(s):  
Mechanical Engineering ◽  
Humanoid Robot ◽  
Industrial Robot ◽  
Science And Technology ◽  
Vice President ◽  
Humanoid Robots ◽  
Real Time Control ◽  
Commercial Development ◽  
Content Type ◽  
The University

Purpose The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD-turned-entrepreneur regarding the commercialization and challenges of bringing a technological invention to market. This paper aims to discuss these issues. Design/methodology/approach The interviewee is Dr Jun Ho Oh, Professor of Mechanical Engineering at the Korea Advanced Institute of Science and Technology (KAIST) and Director of KAIST’s Hubolab. Determined to build a humanoid robot in the early 2000s to compete with Japan’s humanoids, Dr Oh and KAIST created the KHR1. This research led to seven more advanced versions of a biped humanoid robot and the founding of the Robot for Artificial Intelligence and Boundless Walking (Rainbow) Co., a professional technological mechatronics company. In this interview, Dr Oh shares the history and success of Korea’s humanoid robot research. Findings Dr Oh received his BSc in 1977 and MSc in Mechanical Engineering in 1979 from Yonsei University. Oh worked as a Researcher for the Korea Atomic Energy Research Institute before receiving his PhD from the University of California (UC) Berkeley in mechanical engineering in 1985. After his PhD, Oh remained at UC Berkeley to do Postdoctoral research. Since 1985, Oh has been a Professor of Mechanical Engineering at KAIST. He was a Visiting Professor from 1996 to 1997 at the University of Texas Austin. Oh served as the Vice President of KAIST from 2013-2014. In addition to teaching, Oh applied his expertise in robotics, mechatronics, automatic and real-time control to the commercial development of a series of humanoid robots. Originality/value Highly self-motivated and always determined, Dr Oh’s initial dream of building the first Korean humanoid bipedal robot has led him to become one of the world leaders of humanoid robots. He has contributed widely to the field over the nearly past two decades with the development of five versions of the HUBO robot. Oh led Team KAIST to win the 2015 DARPA Robotics Challenge (DRC) and a grand prize of US$2m with its humanoid robot DRC-HUBO+, beating 23 teams from six countries. Oh serves as a robotics policy consultant for the Korean Ministry of Commerce Industry and Energy. He was awarded the 2016 Changjo Medal for Science and Technology, the 2016 Ho-Am Prize for engineering, and the 2010 KAIST Distinguished Professor award. He is a member of the Korea Academy of Science and Technology.

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